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Social determinants of health may help predict sepsis readmission


Global Edition

Artificial Intelligence

Researchers from the University of California, San Diego found that factors such as lack of insurance, economic instability and poor transportation to obtain care were associated with a 30-day readmission. Including social determinants of health in sepsis readmission models could improve their predictive ability, a new study shows.

For the study, published this past week in the Journal of American Medical Informatics Association , University of California, San Diego researchers used data from the National Institutes of Health’s All of Us research program cohort.

They found that including various social determinants of health improved the model’s ability to predict which sepsis patients are at risk of an unplanned 30-day readmission.

“Our results highlight the importance of [social determinants of health] in identifying which patients may benefit from additional resources around the time of discharge, or post-discharge, to prevent 30-day readmissions,” wrote the researchers. WHY IT MATTERS As the researchers noted, 30-day readmissions for sepsis – already a prevalent and potentially deadly condition – are more common and costly than those for several other conditions, including acute myocardial infarction, chronic obstructive pulmonary disease and congestive heart failure.”Improved systems are needed in order to identify those at the highest […]

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